class_docstr: The Missing Values Dispersion visualizer shows the locations of missing (nan)
  values in the feature dataset by the order of the index.
  
  When y targets are supplied to fit, the output dispersion plot is color
  coded according to the target y that the element refers to.
  
  Parameters
  ----------
  alpha : float, default: 0.5
      A value for bending elments with the background.
  
  marker : matplotlib marker, default: |
      The marker used for each element coordinate in the plot
  
  classes : list, default: None
      A list of class names for the legend.
      If classes is None and a y value is passed to fit then the classes
      are selected from the target vector.
  
  kwargs : dict
      Keyword arguments that are passed to the base class and may influence
      the visualization as defined in other Visualizers.
  
  Attributes
  ----------
  features_ : np.array
      The feature labels ranked according to their importance
  
  classes_ : np.array
      The class labels for each of the target values
  
  Examples
  --------
  
  >>> from yellowbrick.contrib.missing import MissingValuesDispersion
  >>> visualizer = MissingValuesDispersion()
  >>> visualizer.fit(X, y=y)
  >>> visualizer.show()
docstr: Called from the fit method, this method creates a scatter plot that
  draws each instance as a class or target colored point, whose location
  is determined by the feature data set.
  
  If y is not None, then it draws a scatter plot where each class is in a
  different color.
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code: def draw(self, X, y, **kwargs):
      """Called from the fit method, this method creates a scatter plot that
      draws each instance as a class or target colored point, whose location
      is determined by the feature data set.
  
      If y is not None, then it draws a scatter plot where each class is in a
      different color.
      """
      nan_locs = self.get_nan_locs()
      if y is None:
          x_, y_ = list(zip(*nan_locs))
          self.ax.scatter(
              x_, y_, alpha=self.alpha, marker=self.marker, label=None
          )
      else:
          self.draw_multi_dispersion_chart(nan_locs)
  
file_path: yellowbrick/yellowbrick/contrib/missing/dispersion.py
imports: import numpy
  from yellowbrick.style.palettes import color_palette
  from .base import MissingDataVisualizer
label_desc: Use image node_id 3 for calling the MissingValuesDispersion obj's underlying member method code with example usage: obj.draw(X, y) without return types